Data Quality & AI Readiness Product Analyst

Job Title: Data Quality & AI Readiness Product Analyst

Job Location: Hyderabad Hub

Job Type: Fulltime/Permanent

About the Job

As a Data Quality & AI Readiness Product Analyst within the MDM Jobs/Skills Taxonomy team — part of Data Governance & Master Data Management — you will sit at the intersection of data governance, Human Capital technology, and process excellence. You will be a critical enabler of Sanofi's enterprise-wide skills-based organization initiative, ensuring that the skills and jobs data powering Workday's Skills Cloud, Career Hub, and AI-driven talent matching is trusted, complete, and AI-ready.

You will drive proactive risk management, resolve global data quality issues, and ensure our Human Capital data meets Sanofi's AI-Ready Data Framework standards — making it fit to power both operational decisions and the AI-driven innovation that underpins our mission to chase the miracles of science.

Main responsibilities

1. Investigation & Diagnosis

• Assess and document downstream impact of Skills and Job Architecture data quality issues across payroll processing, management reporting, third-party integrations, and AI/machine learning model inputs

• Monitor ongoing adoption of global data standards across regions, business units, and functional teams, with particular focus on Skills and Job Architecture taxonomy data consistency in Workday — proactively detecting and flagging the re-introduction of local deviations, non-standard values, or workarounds

• Conduct structured root cause analyses to distinguish isolated errors from systemic issues requiring process or configuration-level intervention

• Use Python scripting and SQL to conduct deep-dive data profiling and root cause investigations across Workday and Snowflake data assets

• Build reusable investigation toolkits and diagnostic scripts to accelerate root cause analysis and reduce time-to-resolution across recurring issue patterns

• Support organizational cloning and data standardization initiatives through fact-based investigation, evidence gathering, and data profiling — ensuring skills data is structured and clean for AI model consumption

• Execute Data Analysis and Mapping for Workday Optimization and other relevant projects

2. Data Quality Engineering & Automation

• Design and build automated Skills and Job Architecture data quality pipelines using Python to validate, profile, and monitor at scale, integrated into the Data Foundation (Snowflake)

• Contribute to the design and implementation of data observability practices — including data lineage tracking, freshness monitoring, and schema validation — across the Skills and Job Architecture data domains

• Build automated monitoring dashboards (e.g., Power BI) and alerting mechanisms to proactively surface data quality deviations before they impact downstream systems, enabling early resolution of cloning/standardization conflicts

3. Data Remediation & Execution

• Develop and execute Python-based remediation scripts and automated correction workflows reducing reliance on manual EIB loads where technically feasible and accelerating remediation

• Prepare, validate, and execute data correction actions and remediation loads (EIB, manual)

• Partner closely with the Global Process Owner (GPO) and Workday Technology teams to define and implement structural fixes — whether through process redesign, system configuration changes, or governance policy updates — and deliver measurable improvement in priority data quality fields

4. Governance, Risk & Stakeholder Collaboration

• Serve as a bridge between data operations and technical teams, translating business data quality requirements into actionable technical specifications aligned with MDM standards

• Identify and escalate risks to data consistency, AI readiness, and global reporting accuracy at the earliest possible stage

• Contribute to AI-Ready Data KPI scoring for the relevant data assets, including DQ rule coverage, quality scoring in Informatica CDGC, metadata cataloging, and data access classification

About You

Required Education, Experience & Skills

• Degree in Information Systems, Data Engineering, Computer Science, Data Management, or a related field

• 3–5 years of experience in data engineering, data quality, data governance, or a related analytical/technical role

• Demonstrated hands-on experience building data pipelines, validation frameworks, or automation scripts in Python

• Proven track record of conducting data investigations and delivering structured, actionable findings

• Experience working in a global, matrixed organization with cross-functional stakeholders

• Strong SQL skills for data profiling, investigation, and validation across large-scale HR datasets

• Experience with big data technologies such as Snowflake

• Experience building and maintaining ELT/ETL pipelines for data quality monitoring and remediation

• Familiarity with data remediation processes, including mass data loads and EIB (Enterprise Interface Builder) or equivalent

• Understanding of HR data domains: employee records, organizational structures, skills profiles, compensation, payroll inputs, and workforce reporting

• Experience with data quality platforms or monitoring tools (e.g., Informatica CDGC, Collibra, Ataccama, or similar)

Preferred Qualifications

• Experience in the pharmaceutical, biotech, or life sciences industry

• Experience working with Workday HCM or comparable enterprise HR platforms is a strong plus — Workday certification or formal training valued but not required as the primary technical requirement

• Familiarity with Workday Skills Cloud, Career Hub and their underlying data structures

• Exposure to MLOps or AI/ML data pipeline engineering

• Certification in data governance, data quality management, or HR analytics

• Knowledge of GDPR, data privacy regulations, and their implications for HR data management

Better is out there. Better medications, better outcomes, better science. But progress doesn’t happen without people – people from different backgrounds, in different locations, doing different roles, all united by one thing: a desire to make miracles happen. So, let’s be those people.

At Sanofi, we provide equal opportunities to all regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, ability or gender identity.

Watch our ALL IN video and check out our Diversity Equity and Inclusion actions at sanofi.com!